activity
20242026
collaborators

8 papers

cs.CL2026

EffGen: Enabling Small Language Models as Capable Autonomous Agents

Gaurav Srivastava, Aafiya Hussain, Chi Wang +2

Most existing language model agentic systems today are built and optimized for large language models (e.g., GPT, Claude, Gemini) via API calls; while powerful, this approach faces…

cs.CL2026

Prompt-Induced Linguistic Fingerprints for LLM-Generated Fake News Detection

Chi Wang, Min Gao, Zongwei Wang +3

With the rapid development of large language models, the generation of fake news has become increasingly effortless, posing a growing societal threat and underscoring the urgent ne…

cs.CL2026

When Does Divide and Conquer Work for Long Context LLM? A Noise Decomposition Framework

Zhen Xu, Shang Zhu, Jue Wang +5

We investigate the challenge of applying Large Language Models (LLMs) to long texts. We propose a theoretical framework that distinguishes the failure modes of long context tasks i…

cs.AI2025

LLM CHESS: Benchmarking Reasoning and Instruction-Following in LLMs through Chess

Sai Kolasani, Maxim Saplin, Nicholas Crispino +5

We introduce LLM CHESS, an evaluation framework designed to probe the generalization of reasoning and instruction-following abilities in large language models (LLMs) through extend…

cs.AI2025

Beyond the Strongest LLM: Multi-Turn Multi-Agent Orchestration vs. Single LLMs on Benchmarks

Aaron Xuxiang Tian, Ruofan Zhang, Jiayao Tang +12

We study multi-turn multi-agent orchestration, where multiple large language model (LLM) agents interact over multiple turns by iteratively proposing answers or casting votes until…

cs.LG2025

Autellix: An Efficient Serving Engine for LLM Agents as General Programs

Michael Luo, Xiaoxiang Shi, Colin Cai +8

Large language model (LLM) applications are evolving beyond simple chatbots into dynamic, general-purpose agentic programs, which scale LLM calls and output tokens to help AI agent…